论文信息 - An artificial neural-based A/D converter using asymmetric Hopfield network

An artificial neural-based A/D converter using asymmetric Hopfield network

The properties of local minima in the energy function of the Tank A/D converter network are studied in detail, and a new design of neural-based A/D converters using asymmetrically connected Hopfield networks has been developed, which can eliminate these local minima completely. The simulated results using SPICE agree well with theoretical analysis of the asymmetric A/D converter.<<ETX>>

Zheng Junli | Zhang Ning

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